Mutations in DNA sequences can cause cancer and aging. Large uncertainties remain about causes of naturally-occurring mutations, and in particular about the importance of DNA replication errors. Furthermore, little is known about strategies used by multicellular organisms to minimize the accumulation of mutations. We will focus on a particular hypothesis that has received widespread recognition but little formal testing. This hypothesis, proposed by John Cairns, postulates that slow- cycling stem cells minimize the average number of divisions that differentiated cells have gone through (that number is a pedigree depth) by periodically refreshing a pool of faster-cycling cells with progenitors that have undergone fewer cycles. By this mechanism, stem cells would minimize replication- dependent mutation accumulation. To measure the importance of DNA replication in mutation accumulation, and to test whether minimization of pedigree depth is naturally used to minimize mutation accumulation, we will leverage a well-defined and highly-tractable stem cell model system: the C. elegans germ line. We will follow two complementary approaches. In a first approach we will develop simple computational simulations of replication-dependent mutation accumulation, and ask what distribution of cell cycle lengths between stem cells and their descendants are predicted by simulations to minimize mutation accumulation. We will progressively expand these models, notably by allowing for a replication-independent source of mutations. We will identify the models that best account for our experimental cell cycle data, and for mutation accumulation data acquired in the second approach. This will allow us to infer the role of DNA replication in mutation accumulation, and the role of cell cycle length control in limiting that accumulation. In a second approach, we will ask if arbitrary changes in germ cell cycle properties alter the dynamics of mutation accumulation and render that accumulation suboptimal. We will first characterize the distribution of cell cycle lengths in key germline regulatory network mutants. We will then develop a critical experimental tool to measure the rate at which mutations accumulate in aging germ lines. The challenge in measuring mutations under natural conditions is that they occur at extremely low frequency. We will thus build a mutation reporter of high sensitivity and extraordinarily-low background. We will use this reporter in wild type and in mutants. This will expand the quantitative basis for our theoretical models, and provide a direct test of the hypothesis that cell cycle length control is used to minimize mutation accumulation. Overall, this work will provide a solid foundation to understand strategies used by multicellular organisms to minimize mutation accumulation with age.